Instructions to use SebastianS/my_mim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SebastianS/my_mim with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="SebastianS/my_mim")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("SebastianS/my_mim")
model = AutoModelForCausalLM.from_pretrained("SebastianS/my_mim", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use SebastianS/my_mim with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SebastianS/my_mim"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SebastianS/my_mim",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/SebastianS/my_mim

SGLang

How to use SebastianS/my_mim with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "SebastianS/my_mim" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SebastianS/my_mim",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "SebastianS/my_mim" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SebastianS/my_mim",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use SebastianS/my_mim with Docker Model Runner:
```
docker model run hf.co/SebastianS/my_mim
```

my_mim

Commit History

Feb 6, 2025

14:55
Adding `safetensors` variant of this model⁠

SFconvertbot

Verified signature
6e43c9f

Nov 13, 2022

00:04
init tokenizer

SebastianS

0f3c837
00:03
init tokenizer

SebastianS

fa2b074

Nov 12, 2022

23:47
Create README.md

SebastianS

45fe7a3
23:47
initial commit

SebastianS

8a4fea8

Commit History

Feb 6, 2025

Adding `safetensors` variant of this model⁠

Nov 13, 2022

init tokenizer

init tokenizer

Nov 12, 2022

Create README.md

initial commit